Recent advance and popularization of smart devices and web application services based on cloud computing have made end-users to directly produce and, at the same time, consume the image contents. This leads to demands of unified contents management services. Thus, this paper proposestag clustering method based on semantic similarity for effective image categorization. We calculate the cost of semantic similarity between tags and cluster tags that are closely related. If tags are in a cluster, we suppose that images with them are also in a same cluster. Furthermore, we could recommend tags for new images on the basis of initial clusters.

In recent years, the number of social network system has grown rapidly. Among them, social bookmarking system(SBS) is one of the most popular systems. SBS provides network platform which users can share and manage various types of online resources by using tags. In SBS, it can be possible to reflect tag and time in order to enhance the quality of personalized recommendation. In this paper, we proposed recommender system which reflect tag and time at weight generation and similarity calculation. Also we adapted proposed method to real dataset and the result of experiment showed that the our method offers better performance when such information is integrated.

In this paper, we propose an activity-performer bipartite matrix generation algorithm for analyzing workflow-supported human-resource affiliations in a workflow model. The workflow-supported human-resource means that all performers of the organization managed by a workflow management system have to be affiliated with a certain set of activities in enacting the corresponding workflow model. We define an activity-performer affiliation network model that is a special type of social networks representing affiliation relationships between a group of performers and a group of activities in workflow models. The algorithm proposed in this paper generates a bipartite matrix from the activity-performer affiliation network model(APANM). Eventually, the generated activity-performer bipartite matrix can be used to analyze social network properties such as, centrality, density, and correlation, and to enable the organization to obtain the workflow-supported human-resource affiliations knowledge.

As the number of podcast users consistently increases which is rising as a new media along with the generalization of SNS and smart devices, the necessity for advanced search service is on the rise. This study designed and implemented a system which recommends a podcast to the users who search podcast by using their social network information. Suggested social network-based podcast search system (PODSSO) collects necessary podcast information only, analyzes social network of the users and makes the users have reliable and interested podcast search results.

In this paper, the combination of ultraviolet and infrared sensors based design for flame signal detection algorithms was proposed with the application of light-wavelength from burning. And, the performance result of image detection was compared by an ultraviolet sensor, an infrared sensor, and the proposed dual-mode sensors(combination of ultraviolet and infrared sensors).

Harvesting energy from the environment is essential for many applications to slow down the deterioration of energy in sensor networks. Energy from the environment is an inexhaustible supply which, if properly managed and harvested from the sources, can allow the system to last for a longer period. Many simulators simulate whole sensor networks where the nodes rely on energy harvesting for their source of power. It is important to be able to assume and simulate a node that can harvest energy from different sources of ambient energy. It is also essential to be able to keep track of the energy levels of the node and adjust node activities based on its energy status. This study aims to develop a prototype for a single node simulator that will show the effects of harvesting from different sources of energy. The results of this study can later be extended for more complicated simulations.

Until now, there have been various studies against Internet worms. Most of intrusion detection and prevention systems against Internet worms use detection rules, but these systems cannot respond to new Internet worms. For this reason, a malicious process control system which uses the fact that Internet worms multicast malicious packets was proposed. However, the greater the number of servers to be protected increases the cost of the malicious process control system, and the probability of detecting Internet worms attacking only some predetermined IP addresses is low. This paper presents a security framework that can reduce the cost of the malicious process control system and increase the probability of detecting Internet worms attacking only some predetermined IP addresses. In the proposed security framework, virtual machines are used to reduce the cost of control servers and unused IP addresses are used to increase the probability of detecting Internet worms attacking only some predetermined IP addresses. Therefore the proposed security framework can effectively respond to a variety of new Internet worms at lower cost.

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, /have been proposed. A typical approach to resolving resource problems of mobile nodes in MCC is to offload functional components to other resource-rich nodes. However, most of the current woks do not consider a characteristic of dynamically changed MCC environment and propose offloading mechanisms in a conceptual level. In this paper, in order to ensure performance of highly complex mobile applications, we propose four different types of offloading mechanisms which can be applied to diverse situations of MCC. And, the proposed offloading mechanisms are practically designed so that they can be implemented with current technologies. Moreover, we define cost models to derive the most sutilable situation of applying each offloading mechanism and prove the performance enhancement through offloadings in a quantitative manner.